IR (Infrared) sensors are widely used in current missile targeting systems (e.g., self-targeting submissiles) to help detect and track target objects in a cluttered background. However, especially in poor weather conditions, the raw image (frame of pixels) data output from the IR sensor may frequently contain a significant portion of non-uniform/fixed pattern noise (FPN) in addition to permanent and blinking dead pixels. These dead pixels are either very bright or dark in intensity leading to non-linear (e.g., saturation or starvation) conditions for the targeting system resulting in low target detection reliability and lower sensor sensitivity. Therefore, many missile targeting systems include a NUC (non-uniform correction) system that attempts to replace the dead pixels and/or reduce the FPN for more reliable target detection (of target signature) and higher sensor sensitivity.
FIG. 1 illustrates an exemplary target detection system 100 found in the prior art that attempts to eliminate and/or reduce the noise and dead pixel problem. During operation, an IR sensor 102, preferably including an FPA (focal plane array), receives the radiant flux from the sensing area and outputs (generates) a raw image data signal 105 (e.g., target signature), at an output voltage (Vp), to amplifier 106 using a capacitor circuit 104. The amplifier 106 outputs a signal (Ve) 107 to an analog-to-digital converter 108 which outputs the digital (response) signal, RIMij 208, to a NUC system 110. The NUC system then performs the process of noise reduction and removing/replacing dead pixel data to help achieve target detection and outputs digital signal CIMij 112.
As shown in FIG. 1, the output image data signal from IR sensor 102 is given by equation 104a where the sensor integration time (IT), given by Ip in the equation 104a, is a critical parameter for producing a high magnitude image signal as input to the amplifier 106. Switching to a longer sensor integration time helps to produce a higher magnitude signal input to the amplifier which aids noise reduction and increases sensor sensitivity leading to early target detection and reliable target tracking and recognition (identification). However, intelligent switching of the integration time must occur since a longer integration time may also lead to system (amplifier) saturation producing undesirable non-linear effects.
Many current targeting systems employ IT switching techniques that switch the integration time continuously on a frame-by-frame basis to maintain input pixel intensity at a middle intensity value to reduce starvation and saturation conditions for the system. However, such frequent IT switching varies the sensor sensitivity and requires more processing power. Additionally, such frequent IT switching to a significant plurality of different values increases calibration complexity for a targeting system when measuring important parameters of a target object (e.g., measured object irradiance needed for target discrimination and classification) since a different calibration is required for each operating IT. Additionally, raw pixel data output from the IR sensor resulting in system saturation should not necessitate a switch to a lower IT since a weak signature (e.g., low temperature) target object may be obscured by nearby bright intensity (e.g., burning) counter-measurement (CM) objects or decoys that produce the saturation condition. Under these conditions, a high or even higher (increased) sensor sensitivity should be maintained and thus the IT should not be switched to a lower value to eliminate the saturation condition.
Therefore, due to the disadvantages of current IT switching approaches, there is a need to provide a dynamic IT switching system that maintains (produces) a high sensor sensitivity without complicating important measurement calibrations and without lowering the reliability of detecting a target object obscured by uninterested objects that produce system saturation.